Results 81 to 90 of about 17,845,866 (289)
dynoGP: Deep Gaussian Processes for Dynamic System Identification
International Journal of Adaptive Control and Signal Processing, EarlyView.This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli +3 more
wiley +1 more source
The Kaldor–Kalecki stochastic model of business cycle
Nonlinear Analysis, 2011 This paper is concerned with the deterministic and the stochastic delayed Kaldor–Kalecki nonlinear business cycle models of the income. They will take into consideration the investment demand in the form suggested by Rodano.
Gabriela Mircea +2 more
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Synapses as stochastic concurrent systems
Theoretical Computer Science, 2008 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Andrea Bracciali +3 more
openaire +4 more sources
Advanced Engineering Materials, EarlyView.Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt +8 more
wiley +1 more source
Stochastic Non Destructive Testing simulation: sensitivity analysis applied to material properties in clogging of nuclear power plant steam generators [PDF]
, 2013 La version éditeur de cette publication est disponible à l'adresse suivante : http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6514684A Non destructive Testing (NDT) procedure is currently used to estimate the clogging of tube support plates in
MOREAU, Olivier +3 more
core +1 more source
Stochastic resonance in Ising systems [PDF]
Physical Review E, 1995 We study by Monte Carlo techniques the evolution of finite two-dimensional Ising systems in oscillating magnetic fields. The phenomenon of stochastic resonance is observed. The characteristic peak obtained for the correlation function between the external field and magnetization, versus the temperature of the system, is studied for various external ...
openaire +3 more sources
What Do Large Language Models Know About Materials?
Advanced Engineering Materials, EarlyView.If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer +2 more
wiley +1 more source
H ? filtering for stochastic singular fuzzy systems with time-varying delay [PDF]
, 2014 This paper considers the H? filtering problem for stochastic singular fuzzy systems with timevarying delay. We assume that the state and measurement are corrupted by stochastic uncertain exogenous disturbance and that the system dynamic is modeled ...
Cai, Min +3 more
core +1 more source
Advanced Engineering Materials, EarlyView.A unified research data management framework for heterogeneous materials data is presented. The system integrates multimodal datasets using ontologies and knowledge graphs, enabling interoperability and FAIR (findable, accessible, interoperable, reusable) data principles. By linking data across scales and workflows, it supports reproducible, Artifitial
Doaa Mohamed +6 more
wiley +1 more source
Filtering for jump-diffusion models by statistical modeling method
Научный вестник МГТУ ГА, 2016 This article develops new methods that reduce the optimal filtering problem for jump-diffusion models to the analysis problem for the special stochastic system with jumps, branching and terminating trajectories. Earlier appropriate methods and algorithms
K. A. Rybakov
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